◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Wenhao Wu

5 papers hereh-index 3335 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author2

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.LG1
same name
  • Wenhao Wu — 27 papers, h 24
  • Wenhao Wu — 12 papers, h 12
  • Wenhao Wu — 8 papers, h 3
  • Wenhao Wu — 5 papers, h 5
  • Wenhao Wu — 4 papers, h 17
  • Wenhao Wu — 4 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedRetrieval Head Mechanistically Explains Long-Context Factuality

1 citations · 1 across the 4 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

LowRankArena: A Standardized Evaluation Platform for SVD-Based LLM Compression

Zishan Shao, Lixun Zhang, Kangning Cui +10

SVD-based low-rank compression has become a fast-growing direction for reducing the memory and computational cost of large language models (LLMs). However, meaningful comparison ac…

cs.CL2025★ 2 cited

A Comprehensive Survey on Long Context Language Modeling

Jiaheng Liu, Dawei Zhu, Zhiqi Bai +34

Efficient processing of long contexts has been a persistent pursuit in Natural Language Processing. With the growing number of long documents, dialogues, and other textual data, it…

cs.CL2024

Long Context Alignment with Short Instructions and Synthesized Positions

Wenhao Wu, Yizhong Wang, Yao Fu +3

Effectively handling instructions with extremely long context remains a challenge for Large Language Models (LLMs), typically necessitating high-quality long data and substantial c…

cs.CL2024★ 1 cited

Retrieval Head Mechanistically Explains Long-Context Factuality

Wenhao Wu, Yizhong Wang, Guangxuan Xiao +2

Despite the recent progress in long-context language models, it remains elusive how transformer-based models exhibit the capability to retrieve relevant information from arbitrary…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.